* Catherine Reyes-Housholder
* Presidentas Rise: Consequences for Women in Cabinets?
* Latin American Politics and Society vol. 58, no. 3 (Fall 2016)

* Note: Unless otherwise specified, models are to be run on  the cabinet dataset with 104 cabinets or the minister dataset with 1,908 ministers.

*Do-File Table of Contents
* 1. TABLE 1 MODEL RESULTS 
* 2. ROBUSTNESS CHECK #1 FEMALE EMPOWERMENT INDICATORS INCLUDED
* 3. ROBUSTNESS CHECK #2 BACHELET 2006 INAUGURAL CABINET REMOVED
* 4. ROBUSTNESS CHECK #3 CLUSTERED STANDARD ERRORS BY PRESIDENT
* 5. ROBUSTNESS CHECK #4 DROP PRESIDENTS WHOSE TERMS ENDED UNEXPECTEDLY 
* 6. ALTERNATIVE EXPLANATION: DO PRESIDENTS MAKE A DIFFERENCE ACCORDING TO MINISTRY PRESTIGE?


* 1. TABLE 1 MODEL RESULTS 

* Full Models OLS (cabinet dataset) *
reg percentfemcab presgen averagecabmasculineportfolio averagecabminprestige femleg predcount farleft left right farright yearappointed cabinetsize  

* Full Models Poisson (cabinet dataset) *
mepoisson countfemcab presgen averagecabmasculineportfolio averagecabminprestige femleg predcount farleft left right farright yearappointed cabinetsize

* Full Models Logistic (minister dataset) *
xtmelogit mingen presgen ministrygender minprestige femleg predcount farleft left right farright yearappointed cabinetsize  || president:

* Inaugural OLS (cabinet dataset) *
reg percentfemcab presgen averagecabmasculineportfolio averagecabminprestige femleg predcount farleft left right farright yearappointed cabinetsize if inaugural==1 

* Inaugural Poisson (cabinet dataset) *
mepoisson countfemcab presgen averagecabmasculineportfolio averagecabminprestige femleg predcount farleft left right farright yearappointed cabinetsize if inaugural==1 

* Inaugural Logistic (minister dataset) *
xtmelogit mingen presgen ministrygender minprestige femleg predcount farleft left right farright yearappointed cabinetsize if inaugural==1 || president:

* End-of-Term OLS (cabinet dataset) *
reg percentfemcab presgen averagecabmasculineportfolio averagecabminprestige femleg predcount farleft left right farright yearappointed cabinetsize if inaugural==0 

* End-of-Term Poisson (cabinet dataset) *
mepoisson countfemcab presgen averagecabmasculineportfolio averagecabminprestige femleg predcount farleft left right farright yearappointed cabinetsize if inaugural==0 

* End-of-Term Logistic (minister dataset) *
xtmelogit mingen presgen ministrygender minprestige femleg predcount farleft left right farright yearappointed cabinetsize if inaugural==0 || president:

* Feminine Logistic (minister dataset) *
xtmelogit mingen presgen minprestige femleg predcount farleft left right farright yearappointed cabinetsize if ministrygender==-1 || president:

* Masculine, Neutral Logistic (minister dataset) *
xtmelogit mingen presgen minprestige femleg predcount farleft left right farright yearappointed cabinetsize if ministrygender~=-1 || president:


* 2. ROBUSTNESS CHECK #1 FEMALE EMPOWERMENT INDICATORS INCLUDED

* Full Models OLS (cabinet dataset) *
reg percentfemcab presgen averagecabmasculineportfolio averagecabminprestige femleg predcount yearappointed farleft left right farright cabinetsize femlaborforce femeducation fertilityrate

* Full Models Poisson (cabinet dataset) *
mepoisson countfemcab presgen averagecabmasculineportfolio averagecabminprestige femleg predcount yearappointed farleft left right farright cabinetsize femlaborforce femeducation fertilityrate

* Full Models Logistic (minister dataset) *
xtmelogit mingen presgen ministrygender minprestige femleg predcount farleft left right farright yearappointed cabinetsize femlaborforce femeducation fertilityrate || president:

* Inaugural OLS (cabinet dataset) *
reg percentfemcab presgen averagecabmasculineportfolio averagecabminprestige femleg predcount yearappointed farleft left right farright cabinetsize femlaborforce femeducation fertilityrate if inaugural==1 

* Inaugural Poisson (cabinet dataset) *
mepoisson countfemcab presgen averagecabmasculineportfolio averagecabminprestige femleg predcount yearappointed farleft left right farright cabinetsize  femlaborforce femeducation fertilityrate if inaugural==1 

* Inaugural Logistic (minister dataset) *
xtmelogit mingen presgen ministrygender minprestige femleg predcount farleft left right farright yearappointed cabinetsize femlaborforce femeducation fertilityrate if inaugural==1 || president:

* End-of-Term OLS (cabinet dataset) *
reg percentfemcab presgen averagecabmasculineportfolio averagecabminprestige femleg predcount yearappointed farleft left right farright cabinetsize femlaborforce femeducation fertilityrate if inaugural==0 

* End-of-Term Poisson (cabinet dataset) *
mepoisson countfemcab presgen averagecabmasculineportfolio averagecabminprestige femleg predcount yearappointed farleft left right farright cabinetsize femlaborforce femeducation fertilityrate if inaugural==0 

* End-of-Term Logistic (minister dataset) *
xtmelogit mingen presgen ministrygender minprestige femleg predcount farleft left right farright yearappointed cabinetsize femlaborforce femeducation fertilityrate if inaugural==0 || president:

* Feminine Logistic (minister dataset) *
xtmelogit mingen presgen minprestige femleg predcount farleft left right farright yearappointed cabinetsize femlaborforce femeducation fertilityrate if ministrygender==-1 || president:

* Masculine, Neutral Logistic (minister dataset) *
xtmelogit mingen presgen minprestige femleg predcount farleft left right farright yearappointed cabinetsize femlaborforce femeducation fertilityrate if ministrygender~=-1 || president:

* 3. ROBUSTNESS CHECK #2 BACHELET 2006 INAUGURAL CABINET REMOVED

* Full Models OLS (cabinet dataset) *
reg percentfemcab presgen averagecabmasculineportfolio averagecabminprestige femleg predcount farleft left right farright yearappointed cabinetsize if bachinauguralcabinet==0 

* Full Models Poisson (cabinet dataset) *
mepoisson countfemcab presgen averagecabmasculineportfolio averagecabminprestige femleg predcount farleft left right farright yearappointed cabinetsize if bachinauguralcabinet==0

* Full Models Logistic (minister dataset) *
xtmelogit mingen presgen ministrygender minprestige femleg predcount farleft left right farright yearappointed cabinetsize if bachinauguralcabinet==0 || president:

* Inaugural OLS (cabinet dataset) *
reg percentfemcab presgen averagecabmasculineportfolio averagecabminprestige femleg predcount farleft left right farright yearappointed cabinetsize if (inaugural==1 & bachinauguralcabinet==0)

* Inaugural Poisson (cabinet dataset) *
mepoisson countfemcab presgen averagecabmasculineportfolio averagecabminprestige femleg predcount farleft left right farright yearappointed cabinetsize if (inaugural==1 & bachinauguralcabinet==0)

* Inaugural Logistic (minister dataset) *
xtmelogit mingen presgen ministrygender minprestige femleg predcount farleft left right farright yearappointed cabinetsize if (inaugural==1 & bachinauguralcabinet==0) || president:

* Feminine Logistic (minister dataset) *
xtmelogit mingen presgen minprestige femleg predcount farleft left right farright yearappointed cabinetsize if (ministrygender==-1 & bachinauguralcabinet==0) || president:

* Masculine, Neutral Logistic (minister dataset) *
xtmelogit mingen presgen minprestige femleg predcount farleft left right farright yearappointed cabinetsize if (ministrygender~=-1 & bachinauguralcabinet==0) || president:


* 4. ROBUSTNESS CHECK #3 CLUSTERED STANDARD ERRORS BY PRESIDENT
logit mingen presgen ministrygender minprestige femleg predcount farleft left right farright yearappointed cabinetsize, cluster(president)
logit mingen presgen ministrygender minprestige femleg predcount farleft left right farright yearappointed cabinetsize if inaugural==1, cluster(president)
logit mingen presgen ministrygender minprestige femleg predcount farleft left right farright yearappointed cabinetsize if inaugural==0, cluster(president)
logit mingen presgen minprestige femleg predcount farleft left right farright yearappointed cabinetsize if ministrygender==-1, cluster(president)
logit mingen presgen minprestige femleg predcount farleft left right farright yearappointed cabinetsize if ministrygender~=-1, cluster(president)


* 5. ROBUSTNESS CHECK #4 DROP PRESIDENTS WHOSE TERMS ENDED UNEXPECTEDLY 
* To obtain these results, you need to drop the following observations in the cabinet and minister datasets: ZELAYA (2006-09), GUTIERREZ (2003-05) AND DE LA RUA (1999-2001), AND GONZALO SANCHEZ DE LA LOZADA (2002-03)).
* These presidents are coded as follows according to variable Presnumber2: Zelaya 42; Gutierrez 91; De La Rua 171; Sanchez de la Lozada 101.
* Once you drop these observations, the cabinets dataset will have 100 cabinets and the minister dataset will have 1,837 ministers.
* Then, run all the Table 1 models on the datasets with 100 cabinets and 1,837 ministers.


* 6. ALTERNATIVE EXPLANATION: DO PRESIDENTS MAKE A DIFFERENCE ACCORDING TO MINISTRY PRESTIGE?

* High prestige
xtmelogit mingen presgen ministrygender femleg predcount farleft left right farright yearappointed cabinetsize if minprestige==3 || president:

* Medium prestige
xtmelogit mingen presgen ministrygender femleg predcount farleft left right farright yearappointed cabinetsize if minprestige==2 || president:

* Low prestige
xtmelogit mingen presgen ministrygender femleg predcount farleft left right farright yearappointed cabinetsize if minprestige==1 || president:

